Priority Coding for video-telephony applications based on visual attention
Date Issued
2006
Abstract
In this paper we investigate the utilization of visual
saliency maps for ROI-based video coding of video-telephony
applications. Visually salient areas indicated in the saliency map
are considered as ROIs. These areas are automatically detected
using an algorithm for visual attention (VA) which builds on the
bottom-up approach proposed by Itti et al. A top-down channel
emulating the visual search for human faces performed by
humans has been added, while orientation, intensity and color
conspicuity maps are computed within a unified multi-resolution
framework based on wavelet subband analysis. Priority encoding,
for experimentation purposes, is utilized in a simple manner:
Frame areas outside the priority regions are blurred using a
smoothing filter and then passed to the video encoder. This leads
to better compression of both Intra-coded (I) frames (more DCT
coefficients are zeroed in the DCT-quantization step) and Inter
coded (P,B) frames (lower prediction error). In more
sophisticated approaches, priority encoding could be
incorporated by varying the quality factor of the DCT
quantization table. Extended experiments concerning both static
images as well as low-quality video show the compression
efficiency of the proposed method. The comparisons are made
against standard JPEG and MPEG-1 encoding respectively.
saliency maps for ROI-based video coding of video-telephony
applications. Visually salient areas indicated in the saliency map
are considered as ROIs. These areas are automatically detected
using an algorithm for visual attention (VA) which builds on the
bottom-up approach proposed by Itti et al. A top-down channel
emulating the visual search for human faces performed by
humans has been added, while orientation, intensity and color
conspicuity maps are computed within a unified multi-resolution
framework based on wavelet subband analysis. Priority encoding,
for experimentation purposes, is utilized in a simple manner:
Frame areas outside the priority regions are blurred using a
smoothing filter and then passed to the video encoder. This leads
to better compression of both Intra-coded (I) frames (more DCT
coefficients are zeroed in the DCT-quantization step) and Inter
coded (P,B) frames (lower prediction error). In more
sophisticated approaches, priority encoding could be
incorporated by varying the quality factor of the DCT
quantization table. Extended experiments concerning both static
images as well as low-quality video show the compression
efficiency of the proposed method. The comparisons are made
against standard JPEG and MPEG-1 encoding respectively.
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